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Field
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, suitable for high I/O and large memory workloads. Mass Data Storage: 2.5 PB of networked storage, plus an additional 150 TB high-speed SSD storage for fast data access. GPU Supercomputing: A GPU server with
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possible. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. We don’t believe in “one-size-fits-all
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and work together to train models, architect systems, and run trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster
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other scalable approximations. Experience running large-scale computations on supercomputers (e.g., SLURM job scripts, GPU acceleration, MPI communication). Notes: This is a full-time, 2 year
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, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data processing or willingness to learn quickly. Publications, thesis work, or demonstrable
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approximations. Experience running large-scale computations on supercomputers (e.g., SLURM job scripts, GPU acceleration, MPI communication). Notes: This is a full-time, 2 year, postdoctoral appointment with
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, evidenced by e.g. projects on Github. Familiarity with deep learning hardware / accelerators and GPU/CUDA kernels.
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for up to 40 employees (heterogeneous operating systems, application programs, GPU clusters, …), communication and cooperation with the Information Technology Services (IT-Center, ZID) Technical support
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Education Centers across Tennessee, providing real-world testbeds for agricultural technology deployment • State-of-the-art computing resources, including high-performance computing (HPC) clusters and GPU
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publications in peer-reviewed journals or conference proceedings, showcasing contributions to the advancement of HPC technologies. Specialized skills in specific areas of HPC, such as GPU programming, quantum